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Dissertations / Theses on the topic 'Edge IoT'

Author: Grafiati

Published: 16 November 2024

Last updated: 25 July 2025

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1

Stiefel, Maximilian. "IOT CONNECTIVITY WITH EDGE COMPUTING." Thesis, Uppsala universitet, Institutionen för informationsteknologi, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-372094.

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Billions of Internet of Things (IoT) devices will be connected in the next decades. Most devices are for Massive Machine Type Communication (MMTC) applications. This requires the IoT infrastructure to be extremely efficient and scalable (like today’s Internet) to support more and more devices connected to the network over time. The cost per connection needs to be very low (like today’s Web services). The current network design with dedicated HW-based base stations (or IoT gateways) may be too costly. Furthermore, there is a vast amount of IoT radio standards, such as Narrowband-IoT (NB-IoT), L

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2

Huang, Zhenqiu. "Progression and Edge Intelligence Framework for IoT Systems." Thesis, University of California, Irvine, 2016. http://pqdtopen.proquest.com/#viewpdf?dispub=10168486.

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<p> This thesis studies the issues of building and managing future Internet of Things (IoT) systems. IoT systems consist of distributed components with services for sensing, processing, and controlling through devices deployed in our living environment as part of the global cyber-physical ecosystem. </p><p> Systems with perpetually running IoT devices may use a lot of energy. One challenge is implementing good management policies for energy saving. In addition, a large scale of devices may be deployed in wide geographical areas through low bandwidth wireless communication networks. This brin

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3

Marchioni, Alex <1989&gt. "Algorithms and Systems for IoT and Edge Computing." Doctoral thesis, Alma Mater Studiorum - Università di Bologna, 2022. http://amsdottorato.unibo.it/10084/1/marchioni_alex_tesi.pdf.

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The idea of distributing the signal processing along the path that starts with the acquisition and ends with the final application has given light to the Internet of Things and Edge Computing, which have demonstrated several advantages in terms of scalability, costs, and reliability. In this dissertation, we focus on designing and implementing algorithms and systems that allow performing a complex task on devices with limited resources. Firstly, we assess the trade-off between compression and anomaly detection from both a theoretical and a practical point of view. Information theory provide

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4

Antonini, Mattia. "From Edge Computing to Edge Intelligence: exploring novel design approaches to intelligent IoT applications." Doctoral thesis, Università degli studi di Trento, 2021. http://hdl.handle.net/11572/308630.

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The Internet of Things (IoT) has deeply changed how we interact with our world. Today, smart homes, self-driving cars, connected industries, and wearables are just a few mainstream applications where IoT plays the role of enabling technology. When IoT became popular, Cloud Computing was already a mature technology able to deliver the computing resources necessary to execute heavy tasks (e.g., data analytic, storage, AI tasks, etc.) on data coming from IoT devices, thus practitioners started to design and implement their applications exploiting this approach. However, after a hype that lasted f

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Antonini, Mattia. "From Edge Computing to Edge Intelligence: exploring novel design approaches to intelligent IoT applications." Doctoral thesis, Università degli studi di Trento, 2021. http://hdl.handle.net/11572/308630.

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The Internet of Things (IoT) has deeply changed how we interact with our world. Today, smart homes, self-driving cars, connected industries, and wearables are just a few mainstream applications where IoT plays the role of enabling technology. When IoT became popular, Cloud Computing was already a mature technology able to deliver the computing resources necessary to execute heavy tasks (e.g., data analytic, storage, AI tasks, etc.) on data coming from IoT devices, thus practitioners started to design and implement their applications exploiting this approach. However, after a hype that lasted f

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6

Piscaglia, Daniele. "Supporto e Infrastrutture DevOps per Microservizi IoT su Edge Gateway." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2021.

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Progetto svolto durante il tirocinio presso l'azienda Bonfiglioli Riduttori che descrive il processo di modifica di una soluzione di predictive maintenance esistente. La soluzione che coinvolge sensori IoT per la raccolta dati e Edge gateway per analisi e processamento, è stata rivisitata in funzione di importanti meccaniche di amministrazione e manutenzione. Il focus principale della tesi è su come questi sistemi distribuiti richiedano un approccio differente alla distribuzione dei microservizi e alla gestione dei dispositivi e come l'utilizzo delle varie tipologie di piattaforme IoT possano

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7

Broumas, Ioannis. "Design of Cellular and GNSS Antenna for IoT Edge Device." Thesis, Högskolan i Halmstad, Akademin för informationsteknologi, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:hh:diva-39239.

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Antennas are one of the most sensitive elements in any wireless communication equipment. Designing small-profile, multiband and wideband internal antennas with a simple structure has become a necessary challenge. In this thesis, two planar antennas are designed, simulated and implemented on an effort to cover the LTE-M1 and NB-IoT radio frequencies. The cellular antenna is designed to receive and transmit data over the eight-band LTE700/GSM/UMTS, and the GNSS antenna is designed to receive signal from the global positioning system and global navigation systems, GPS (USA) and GLONASS. The anten

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8

Ashouri, Majid. "Towards Supporting IoT System Designers in Edge Computing Deployment Decisions." Licentiate thesis, Malmö universitet, Malmö högskola, Institutionen för datavetenskap och medieteknik (DVMT), 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:mau:diva-37068.

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The rapidly evolving Internet of Things (IoT) systems demands addressing new requirements. This particularly needs efficient deployment of IoT systems to meet the quality requirements such as latency, energy consumption, privacy, and bandwidth utilization. The increasing availability of computational resources close to the edge has prompted the idea of using these for distributed computing and storage, known as edge computing. Edge computing may help and complement cloud computing to facilitate deployment of IoT systems and improve their quality. However, deciding where to deploy the various a

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9

Rajakaruna, A. (Archana). "Lightweight edge-based networking architecture for low-power IoT devices." Master's thesis, University of Oulu, 2019. http://jultika.oulu.fi/Record/nbnfioulu-201906072483.

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Abstract. The involvement of low power Internet of Things (IoT) devices in the Wireless Sensor Networks (WSN) allow enhanced autonomous monitoring capability in many application areas. Recently, the principles of edge computing paradigm have been used to cater onsite processing and managing actions in WSNs. However, WSNs deployed in remote sites require human involvement in data collection process since internet accessibility is still limited to population dense areas. Nowadays, researchers propose UAVs for monitoring applications where human involvement is required frequently. In this thesis

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10

KOBEISSI, AHMAD. "VERSO IL CONCETTO DI SMART CITY: SOLUZIONI IOT EDGE-CLOUD." Doctoral thesis, Università degli studi di Genova, 2020. http://hdl.handle.net/11567/996248.

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Since the term was coined by Kevin Ashton in 1999, the Internet of Things (IoT) did not gain considerable popularity until 2010 where it became a strategic priority for governments, companies, and research centers. Despite this large-scale interest, IoT only reached mass markets in 2014 in the form of wearable devices and fitness trackers, home automation, industrial asset monitoring, and smart energy meters. The ‘things’ refer to sensors and other smart devices with the ability to monitor an object’s state, or even control it using actuators. Ashton envisaged that when such sensors and smart

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Sellami, Youssef. "Secure data management in an IoT-Fog/Edge computing architecture." Electronic Thesis or Diss., Valenciennes, Université Polytechnique Hauts-de-France, 2024. https://ged.uphf.fr/nuxeo/site/esupversions/14bb8a1d-7fbb-4d10-a7e7-99650617c232.

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L'internet des objets vise à intégrer les mondes physique et numérique dans un écosystème unique en interconnectant un grand nombre d'objets intelligents (capteurs, smartphones, véhicules autonomes, etc.) à l'internet. Cependant, la quantité massive de données est l'une des conséquences inévitables de la croissance du nombre d'objets connectés. L'évolution de l'IoT et de ses applications dans les années à venir (industrie 4.0, villes intelligentes) nécessite une gestion des données adaptée aux capacités limitées des objets connectés. De nouveaux paradigmes de traitement et de communication, te

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12

Ghaffar, Talha. "Empirical Evaluation of Edge Computing for Smart Building Streaming IoT Applications." Thesis, Virginia Tech, 2019. http://hdl.handle.net/10919/88438.

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Smart buildings are one of the most important emerging applications of Internet of Things (IoT). The astronomical growth in IoT devices, data generated from these devices and ubiquitous connectivity have given rise to a new computing paradigm, referred to as "Edge computing", which argues for data analysis to be performed at the "edge" of the IoT infrastructure, near the data source. The development of efficient Edge computing systems must be based on advanced understanding of performance benefits that Edge computing can offer. The goal of this work is to develop this understanding by examinin

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Eriksson, Fredrik, and Sebastian Grunditz. "Containerizing WebAssembly : Considering WebAssembly Containers on IoT Devices as Edge Solution." Thesis, Linköpings universitet, Institutionen för datavetenskap, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-177581.

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This paper will explore the speed of execution, memory foot-print and the maturity of WebAssembly Runtimes (WasmRT).For this study, the WasmRT will be Wasmer1and Wasmtime.2Initially, benchmarks were run on a Raspberry Pi 3 model Bto simulate a more hardware capable IoT-device. Tests per-formed on a Raspberry Pi shows that there are many instanceswhere a WasmRT outperforms a similar Docker+C solution.WasmRT has a very clear use case for IoT devices, specifi-cally short jobs, the results from our research will show thatWasmRT can be up to almost 70 times as fast as a similarDocker solution. Wasm

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14

Liu, Sige. "Bandit Learning Enabled Task Offloading and Resource Allocation in Mobile Edge Computing." Thesis, The University of Sydney, 2022. https://hdl.handle.net/2123/29719.

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The Internet-of-Things (IoT) is envisioned as a promising paradigm for carrying the interconnections of massive devices through various communications protocols. With the rapid development of fifth-generation (5G), IoT has incentivized a large number of new computation-intensive applications and bridges diverse technologies to provide ubiquitous services with intelligence. However, with billions of devices anticipated to be connected in IoT systems in the coming years, IoT devices face a series of challenges from their inherent features. For instance, the IoT devices are usually densely depl

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15

Laroui, Mohammed. "Distributed edge computing for enhanced IoT devices and new generation network efficiency." Electronic Thesis or Diss., Université Paris Cité, 2022. http://www.theses.fr/2022UNIP7078.

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Dans le cloud computing, les services et les ressources sont centralisés dans des centres de données auxquels l’utilisateur peut accéder à partir de ses appareils connectés. L’infrastructure cloud traditionnelle sera confrontée à une série de défis en raison de la centralisation de calcul, du stockage et de la mise en réseau dans un petit nombre de centres de données, et de la longue distance entre les appareils connectés et les centres de données distants. Pour répondre à ce besoin, l’edge computing s’appuie sur un modèle dans lequel les ressources de calcul sont distribuées dans le edge de r

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Samikwa, Eric. "Flood Prediction System Using IoT and Artificial Neural Networks with Edge Computing." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-280299.

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Flood disasters affect millions of people across the world by causing severe loss of life and colossal damage to property. Internet of things (IoT) has been applied in areas such as flood prediction, flood monitoring, flood detection, etc. Although IoT technologies cannot stop the occurrence of flood disasters, they are exceptionally valuable apparatus for conveyance of catastrophe readiness and counteractive action data. Advances have been made in flood prediction using artificial neural networks (ANN). Despite the various advancements in flood prediction systems through the use of ANN, there

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Garofalo, Angelo <1993&gt. "Flexible Computing Systems For AI Acceleration At The Extreme Edge Of The IoT." Doctoral thesis, Alma Mater Studiorum - Università di Bologna, 2022. http://amsdottorato.unibo.it/10288/1/PhD_Thesis_Angelo_Garofalo_ETIT_34.pdf.

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Embedding intelligence in extreme edge devices allows distilling raw data acquired from sensors into actionable information, directly on IoT end-nodes. This computing paradigm, in which end-nodes no longer depend entirely on the Cloud, offers undeniable benefits, driving a large research area (TinyML) to deploy leading Machine Learning (ML) algorithms on micro-controller class of devices. To fit the limited memory storage capability of these tiny platforms, full-precision Deep Neural Networks (DNNs) are compressed by representing their data down to byte and sub-byte formats, in the integer

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18

Bassi, Lorenzo. "Orchestration of a MEC-based multi-protocol IoT environment." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2021. http://amslaurea.unibo.it/24114/.

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Nowadays we are witnessing to a continuous increasing of the number of IoT devices that must be configured and supported by modern networks. Considering an industrial environment, there is a huge number of these devices that need to coexist at the same time. Each one of them is using its own communication/transport protocol, and a huge effort needs to be done during the setup of the system. In addition, there are also different kind of architectures that can be used. That’s why the network setup is not so easy in this kind of heterogeneous environment. The answer to all these problems can be

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19

Raffa, Viviana. "Edge/cloud virtualization techniques and resources allocation algorithms for IoT-based smart energy applications." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2021. http://amslaurea.unibo.it/22864/.

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Nowadays, the installation of residential battery energy storage (BES) has increased as a consequence of the decrease in the cost of batteries. The coupling of small-scale energy generation (residential PV) and residential BES promotes the integration of microgrids (MG), i.e., clusters of local energy sources, energy storages, and customers which are represented as a single controllable entity. The operations between multiple grid-connected MGs and the distribution network can be coordinated by controlling the power exchange; however, in order to achieve this level of coordination, a co

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AGUIARI, DAVIDE. "Exploring Computing Continuum in IoT Systems: Sensing, Communicating and Processing at the Network Edge." Doctoral thesis, Università degli Studi di Cagliari, 2021. http://hdl.handle.net/11584/311478.

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As Internet of Things (IoT), originally comprising of only a few simple sensing devices, reaches 34 billion units by the end of 2020, they cannot be defined as merely monitoring sensors anymore. IoT capabilities have been improved in recent years as relatively large internal computation and storage capacity are becoming a commodity. In the early days of IoT, processing and storage were typically performed in cloud. New IoT architectures are able to perform complex tasks directly on-device, thus enabling the concept of an extended computational continuum. Real-time critical scenarios e.g. auton

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Aguiari, Davide. "Exploring Computing Continuum in IoT Systems : sensing, communicating and processing at the Network Edge." Electronic Thesis or Diss., Sorbonne université, 2021. http://www.theses.fr/2021SORUS131.

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L'Internet des objets (IoT), ne comprenant à l'origine que quelques dispositifs de détection simple, atteint aujourd’hui 34 milliards d’objets connectés d'ici fin 2020. Ces objets ne peuvent plus être définis comme de simples capteurs de surveillance. Les capacités de l'IoT ont été améliorées ces dernières années tandis-que que les capacités de calcul et de stockage de masse sont devenus des marchandises. Aux débuts de l'IoT, le traitement et le stockage étaient généralement effectués dans le cloud. Les nouvelles architectures IoT sont capables d'exécuter des tâches complexes directement sur l

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Xia, Chunqiu. "Energy Demand Response Management in Smart Home Environments." Thesis, The University of Sydney, 2018. http://hdl.handle.net/2123/20182.

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ENABLING DEMAND RESPONSE ON ENERGY MANAGEMENT IN SMART HOME With the penetration of the Internet of Things (IoT) paradigm into the household scenario, an increasing number of smart appliances have been deployed to improve the comfort of living in the household. At present, most smart home devices are adopting the Cloud-based paradigm. The increasing electricity overhead from these smart appliances, however, has caused issues, as existing home energy management systems are unable to reduce electricity consumption effectively. To address this issue, we propose the use of an Edge-based computing

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Shirin, Abkenar Forough. "Towards Hyper-efficient IoT Networks Using Fog Paradigm." Thesis, The University of Sydney, 2022. https://hdl.handle.net/2123/28951.

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Fog computing was emerged as a treasured paradigm to improve the efficiency of the typical cloud of things (CoT) architecture of the Internet of Things (IoT) networks. Contrasting to the CoT in which the resource-rich high-performance data centers (DCs) are located far from the energy-constrained terminal nodes (TNs), fog nodes (FNs) in fog-enabled architecture provide computing resources in the proximity of the TNs. Therefore, the TNs consume less energy to offload their generated tasks to the FNs rather than the cloud DCs. Moreover, shortening the distance between the TNs and the FNs results

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Ozeer, Umar Ibn Zaid. "Autonomic resilience of distributed IoT applications in the Fog." Thesis, Université Grenoble Alpes (ComUE), 2019. http://www.theses.fr/2019GREAM054.

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Les dernières tendances de l'informatique distribuées préconisent le Fog computing quiétend les capacités du Cloud en bordure du réseau, à proximité des objets terminaux etdes utilisateurs finaux localisé dans le monde physique. Le Fog est un catalyseur clé desapplications de l'Internet des Objets (IoT), car il résout certains des besoins que le Cloud neparvient à satisfaire, tels que les faibles latences, la confidentialité des données sensibles, laqualité de service ainsi que les contraintes géographiques. Pour cette raison, le Fog devientde plus en plus populaire et trouve des cas d'utilisa

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Samie, Farzad [Verfasser], and J. [Akademischer Betreuer] Henkel. "Resource Management for Edge Computing in Internet of Things (IoT) / Farzad Samie ; Betreuer: J. Henkel." Karlsruhe : KIT-Bibliothek, 2018. http://d-nb.info/1154856690/34.

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Mestoukirdi, Mohamad. "Reliable and Communication-Efficient Federated Learning for Future Intelligent Edge Networks." Electronic Thesis or Diss., Sorbonne université, 2023. http://www.theses.fr/2023SORUS432.

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Dans le domaine des futurs réseaux sans fil 6G, l'intégration de la périphérie intelligente grâce à l'avènement de l'IA représente un bond en avant considérable, promettant des avancées révolutionnaires en matière de communication sans fil. Cette intégration favorise une synergie harmonieuse, capitalisant sur le potentiel collectif de ces technologies transformatrices. Au cœur de cette intégration se trouve le rôle de l'apprentissage fédéré, un paradigme d'apprentissage décentralisé qui préserve la confidentialité des données tout en exploitant l'intelligence collective des appareils interconn

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Perala, Sai Saketh Nandan. "Efficient Resource Management for Video Applications in the Era of Internet-of-Things (IoT)." OpenSIUC, 2018. https://opensiuc.lib.siu.edu/theses/2311.

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The Internet-of-Things (IoT) is a network of interconnected devices with sensing, monitoring and processing functionalities that work in a cooperative way to offer services. Smart buildings, self-driving cars, house monitoring and management, city electricity and pollution monitoring are some examples where IoT systems have been already deployed. Amongst different kinds of devices in IoT, cameras play a vital role, since they can capture rich and resourceful content. However, since multiple IoT devices share the same gateway, the data that is produced from high definition cameras congest the n

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Tania, Zannatun Nayem. "Machine Learning with Reconfigurable Privacy on Resource-Limited Edge Computing Devices." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-292105.

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Distributed computing allows effective data storage, processing and retrieval but it poses security and privacy issues. Sensors are the cornerstone of the IoT-based pipelines, since they constantly capture data until it can be analyzed at the central cloud resources. However, these sensor nodes are often constrained by limited resources. Ideally, it is desired to make all the collected data features private but due to resource limitations, it may not always be possible. Making all the features private may cause overutilization of resources, which would in turn affect the performance of the who

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Sigwele, Tshiamo, Yim Fun Hu, M. Ali, Jiachen Hou, M. Susanto, and H. Fitriawan. "An intelligent edge computing based semantic gateway for healthcare systems interoperability and collaboration." IEEE, 2018. http://hdl.handle.net/10454/17552.

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Yes<br>The use of Information and Communications Technology (ICTs) in healthcare has the potential of minimizing medical errors, reducing healthcare cost and improving collaboration between healthcare systems which can dramatically improve the healthcare service quality. However interoperability within different healthcare systems (clinics/hospitals/pharmacies) remains an issue of further research due to a lack of collaboration and exchange of healthcare information. To solve this problem, cross healthcare system collaboration is required. This paper proposes a conceptual semantic based health

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Monducci, Francesca. "Infrastruttura Edge-based per Sistemi Predittivi in Ambito Industriale." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2021. http://amslaurea.unibo.it/24054/.

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Il continuo evolversi della tecnologia ha portato nel corso della storia a diverse rivoluzioni industriali, la cui ultima è la così detta Industria 4.0. Con Industria 4.0 vengono integrate alcune nuove tecnologie mirate al miglioramento delle condizioni di lavoro, alla creazione di nuovi modelli di business e un generale aumento della produttività e della qualità. Alla base di questa rivoluzione industriale si trova l'IoT, che permette la raccolta di grandi quantità di dati, come ad esempio i comportamenti delle macchine industriali. Passando all'elaborazione di questi dati è possibile creare

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Vargas, Vargas Fernando. "Cloudlet for the Internet-of- Things." Thesis, KTH, Skolan för informations- och kommunikationsteknik (ICT), 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-191433.

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With an increasing number of people currently living in urban areas, many cities around the globe are faced with issues such as increased pollution and traffic congestion. In an effort to tackle such challenges, governments and city councils are formulating new and innovative strategies. The integration of ICT with these strategies creates the concept of smart cities. The Internet of Things (IoT) is a key driver for smart city initiatives, making it necessary to have an IT infrastructure that can take advantage of the many benefits that IoT can provide. The Cloudlet is a new infrastructure mod

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Vadivelu, Somasundaram. "Sensor data computation in a heavy vehicle environment : An Edge computation approach." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-235486.

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In a heavy vehicle, internet connection is not reliable, primarily because the truck often travels to a remote location where network might not be available. The data generated from the sensors in a vehicle might not be sent to the internet when the connection is poor and hence it would be appropriate to store and do some basic computation on those data in the heavy vehicle itself and send it to the cloud when there is a good network connection. The process of doing computation near the place where data is generated is called Edge computing. Scania has its own Edge computation solution, which

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Longo, Eugenio. "AI e IoT: contesto e stato dell’arte." Bachelor's thesis, Alma Mater Studiorum - Università di Bologna, 2022.

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L’intelligenza artificiale costituisce un ramo dell’informatica che permette di programmare e progettare sistemi in grado di dotare le macchine di caratteristiche considerate tipicamente umane. L’internet delle cose rappresenta una rete di oggetti fisici in grado di connettersi e scambiare dati con altri dispositivi tramite internet. Nonostante L’internet delle cose e l’intelligenza artificiale rappresentino due concetti diversi, riescono ad integrarsi per creare nuove soluzioni con un elevato potenziale. L’utilizzo combinato di queste due tecnologie permette di aumentare il valore di entrambe

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Sirigu, Giovanni. "Progettazione di Gateway Edge per Smart Factory." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2019. http://amslaurea.unibo.it/17589/.

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Il presente lavoro di tesi riguarda la progettazione e realizzazione di un Gateway Edge programmabile per la Smart Factory che consenta il monitoraggio di macchine industriali, con lo scopo di integrarle con i sistemi informativi aziendali. Il sistema sviluppato presenta come nucleo il Raspberry-Pi model 3 B+ al quale vengono integrate una serie di interfacce di comunicazione wireless e cablate ed interfacce I/O sia di tipo analogico che digitale. Il lavoro ha avuto inizio con lo studio del mondo IoT e del mondo Smart Factory il quale ha portato alla progettazione hardware del Gateway Edge.

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Rahman, Hasibur. "Distributed Intelligence-Assisted Autonomic Context-Information Management : A context-based approach to handling vast amounts of heterogeneous IoT data." Doctoral thesis, Stockholms universitet, Institutionen för data- och systemvetenskap, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:su:diva-149513.

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As an implication of rapid growth in Internet-of-Things (IoT) data, current focus has shifted towards utilizing and analysing the data in order to make sense of the data. The aim of which is to make instantaneous, automated, and informed decisions that will drive the future IoT. This corresponds to extracting and applying knowledge from IoT data which brings both a substantial challenge and high value. Context plays an important role in reaping value from data, and is capable of countering the IoT data challenges. The management of heterogeneous contextualized data is infeasible and insufficie

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Passeri, Luca. "Pervasive Jarvis: Evoluzione di un Sistema IoT per le Smart Home." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2020.

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L'enorme crescita dell'Internet of Things ha permesso una trasformazione degli ambienti in cui viviamo tramite la diffusione di dispositivi sempre più intelligenti, in grado di interagire tra loro e con il mondo esterno. In questo scenario si introduce Jarvis, un assistente virtuale per case ed uffici. Jarvis integra diversi prodotti e servizi, mettendo a disposizione dell'utente numerose funzionalità che permettono di automatizzare un'abitazione e controllarla da remoto. Questo progetto si propone di evolvere Jarvis rendendolo conforme allo standard attuale dei sistemi IoT per le smart home

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Harmassi, Mariem. "Thing-to-thing context-awareness at the edge." Thesis, La Rochelle, 2019. http://www.theses.fr/2019LAROS037.

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L'Internet des objets (IdO) comprend aujourd'hui une riche offre d'objets connectés, qui permettent de collecter et de partager en continu des données hétérogènes se rapportant à leurs environnements. Ceci a permis l'émergence d'un nouveau type d'applications, qui sont basées sur ces données et permettent de faciliter la vie des citoyens. Ces applications de l'Internet des objets sont dites « sensibles au contexte ». Grâce aux données collectées sur le contexte de l'utilisateur, elles sont en mesure d'adapter leur comportement de manière autonome, sans intervention humaine. Dans cette thèse, n

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Le, Xuan Sang. "Co-conception Logiciel/FPGA pour Edge-computing : promotion de la conception orientée objet." Thesis, Brest, 2017. http://www.theses.fr/2017BRES0041/document.

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L’informatique en nuage (cloud computing) est souvent le modèle de calcul le plus référencé pour l’internet des objets (Internet of Things).Ce modèle adopte une architecture où toutes les données de capteur sont stockées et traitées de façon centralisée. Malgré de nombreux avantages, cette architecture souffre d’une faible évolutivité alors même que les données disponibles sur le réseau sont en constante augmentation. Il est à noter que, déjà actuellement, plus de50 % des connexions sur Internet sont inter objets. Cela peut engendrer un problème de fiabilité dans les applications temps réel. L

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Miccoli, Roberta. "Implementation of a complete sensor data collection and edge-cloud communication workflow within the WeLight project." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2021. http://amslaurea.unibo.it/22563/.

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This thesis aims at developing the full workflow of data collection from a laser sensor connected to a mobile application, working as edge device, which subsequently transmits the data to a Cloud platform for analysing and processing. The project is part of the We Light (WErable LIGHTing for smart apparels) project, in collaboration with TTLab of the INFN (National Institute of Nuclear Physics). The goal of We Light is to create an intelligent sports shirt, equipped with sensors that take information from the external environment and send it to a mobile device. The latter then sends the data v

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Hvizdák, Lukáš. "Systém sběru dat v průmyslu." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2020. http://www.nusl.cz/ntk/nusl-413269.

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The master thesis focuses on the design and implementation of data collection from production using a PLC into an SQL database located in the cloud and subsequent visualization. The work describes the applicable communication protocols MQTT and OPC UA with the fact that the protocol MQTT was selected. It deals with securing data transfer from the line to the cloud using the TLS protocol. The individual cloud services and their possibilities for data collection are described here. The work deals with the possibilities of data visualization using existing open source solutions and the difference

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Cantamaglia, Carlo. "Progettazione e sviluppo di un sistema di aggregazione dati per applicazioni WoT in uno scenario di monitoraggio strutturale." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2021. http://amslaurea.unibo.it/22866/.

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Il monitoraggio della salute strutturale (SHM) sta diventando un argomento di ricerca cruciale per migliorare la sicurezza umana e ridurre i costi di manutenzione. Nonostante la forte crescita delle applicazioni Web of Things in quest'ambito restano ancora irrisolti problemi come il pre-processamento di dati e la migrazione di servizi tra Cloud ed Edge. Il seguente lavoro offre una soluzione ai suddetti problemi, progettando e sviluppando un sistema di aggregazione WoT che sia in grado di calcolare metriche e attuare politiche di migrazioni diverse in base al caso specifico. Infine, il si

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Li, Hengsha. "Real-time Cloudlet PaaS for GreenIoT : Design of a scalable server PaaS and a GreenIoT application." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-239004.

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Cloudlet is a recent topic that has attained much interest in network system research. It can be characterized as a PaaS (Platform as a Service) layer that allows mobile clients to execute their code in the cloud. Cloudlet can be seen as a layer at the edge of the communication network.In this thesis, we present a cloudlet architecture design which includes cloudlet code as a part of client application itself. We first provide an overview of related work and describe existing challenges which need to be addressed. Next, we present an overview design for a cloudlet-based implementation. Finally

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Jouni, Zalfa. "Analog spike-based neuromorphic computing for low-power smart IoT applications." Electronic Thesis or Diss., université Paris-Saclay, 2024. http://www.theses.fr/2024UPAST114.

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Avec l'expansion de l'Internet des objets (IoT) et l'augmentation des appareils connectés et des communications complexes, la demande de technologies de localisation précises et économes en énergie s'est intensifiée. Les techniques traditionnelles de machine learning et d'intelligence artificielle (IA) offrent une haute précision dans la localisation par radiofréquence (RF), mais au prix d'une complexité accrue et d'une consommation d'énergie élevée. Pour relever ces défis, cette thèse explore le potentiel de l'informatique neuromorphique, inspirée par les mécanismes du cerveau, pour permettre

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Feraudo, Angelo. "Distributed Federated Learning in Manufacturer Usage Description (MUD) Deployment Environments." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2020.

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Il costante avanzamento dei dispositivi Internet of Things (IoT) in diversi ambienti, ha provocato la necessità di nuovi meccanismi di sicurezza e monitoraggio in una rete. Tali dispositvi sono spesso considerati fonti di vulnerabilità sfruttabili da malintenzionati per accedere alla rete o condurre altri attacchi. Questo è dovuto alla natura stessa dei dispositivi, ovvero offrire servizi aventi a che fare con dati sensibili (p.es. videocamere) seppur con risorse molto limitate. Una soluzione in questa direzione, è l'impiego della specifica Manufacturer Usage Description (MUD), che impone al m

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Maltoni, Pietro. "Progetto di un acceleratore hardware per layer di convoluzioni depthwise in applicazioni di Deep Neural Network." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2021. http://amslaurea.unibo.it/24205/.

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Il progressivo sviluppo tecnologico e il costante monitoraggio, controllo e analisi della realtà circostante ha condotto allo sviluppo di dispositivi IoT sempre più performanti, per questo si è iniziato a parlare di Edge Computing. In questi dispositivi sono presenti le risorse per elaborare i dati dai sensori direttamente in locale. Questa tecnologia si adatta bene alle CNN, reti neurali per l'analisi e il riconoscimento di immagini. Le Separable Convolution rappresentano una nuova frontiera perchè permettono di diminuire in modo massiccio la quantità di operazioni da eseguire su tensori di d

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Gandolfi, Riccardo. "Design of a memory-to-memory tensor reshuffle unit for ultra-low-power deep learning accelerators." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2021. http://amslaurea.unibo.it/23706/.

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In the context of IoT edge-processing, deep learning applications and near-sensor analytics, the constraints on having low area occupation and low power consumption in MCUs (Microcontroller Units) performing computationally intensive tasks are more stringent than ever. A promising direction is to develop HWPEs (Hardware Processing Engines) that support and help the end-node in the execution of these tasks. The following work concerns the design and testing of the Datamover, a small and easily configurable HWPE for tensor shuffling and data marshaling operation. The accelerator is to be integra

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Rahafrouz, Amir. "Distributed Orchestration Framework for Fog Computing." Thesis, Luleå tekniska universitet, Institutionen för system- och rymdteknik, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:ltu:diva-77118.

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The rise of IoT-based system is making an impact on our daily lives and environment. Fog Computing is a paradigm to utilize IoT data and process them at the first hop of access network instead of distant clouds, and it is going to bring promising applications for us. A mature framework for fog computing still lacks until today. In this study, we propose an approach for monitoring fog nodes in a distributed system using the FogFlow framework. We extend the functionality of FogFlow by adding the monitoring capability of Docker containers using cAdvisor. We use Prometheus for collecting distribut

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Sinigaglia, Mattia. "Progettazione ed implementazione di un Sistema On Chip per applicazioni audio." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2021. http://amslaurea.unibo.it/23790/.

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Lo scopo de progetto è stato quello di contribuire alla realizzazione di un microcontrollore progettato per applicazioni audio con bassissimi consumi. Il microcontrollore integra un acceleratore FFT che effettua la trasformata di Fourier su diversi segnali audio acquisiti dalla periferica I2S che è una periferica dedicata alla comunicazione con interfacce audio digitali. Nello specifico, è stato implementato nella periferica I2S il protocollo DSP con TDM per consentire la connessione di molteplici dispositivi sulla stessa linea dati. Il risultato ottenuto è stato quello di riuscire a comunica

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Busacca, Fabio Antonino. "AI for Resource Allocation and Resource Allocation for AI: a two-fold paradigm at the network edge." Doctoral thesis, Università degli Studi di Palermo, 2022. https://hdl.handle.net/10447/573371.

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5G-and-beyond and Internet of Things (IoT) technologies are pushing a shift from the classic cloud-centric view of the network to a new edge-centric vision. In such a perspective, the computation, communication and storage resources are moved closer to the user, to the benefit of network responsiveness/latency, and of an improved context-awareness, that is, the ability to tailor the network services to the live user's experience. However, these improvements do not come for free: edge networks are highly constrained, and do not match the resource abundance of their cloud counterparts. In such a

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Kheffache, Mansour. "Energy-Efficient Detection of Atrial Fibrillation in the Context of Resource-Restrained Devices." Thesis, Luleå tekniska universitet, Datavetenskap, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:ltu:diva-76394.

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eHealth is a recently emerging practice at the intersection between the ICT and healthcare fields where computing and communication technology is used to improve the traditional healthcare processes or create new opportunities to provide better health services, and eHealth can be considered under the umbrella of the Internet of Things. A common practice in eHealth is the use of machine learning for a computer-aided diagnosis, where an algorithm would be fed some biomedical signal to provide a diagnosis, in the same way a trained radiologist would do. This work considers the task of Atrial Fibr

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